Gotta love surfing past an article entitled, “40 Books You Must Read.”
Must read… or what? Or I get several weeks of my life back by avoiding a bunch of books that some clickbait told me about?
Managers tasked with analytics adoption are busy: it’s a constantly-evolving field in a topsy-turvy market. That said, it’s wise for them to crack the books and learn from time to time: after all, analytics adoption at most organizations, according to Harvard Business Review, is going abysmally.
Here are just three books I recommend analytics managers read: no pressure, no hex spells. You can even skim the last one!
The final, bonus resource, however, is not to be missed.
1. Creating a Data-Driven Organization
![Cover of Creating a data-driven organization](https://i0.wp.com/georgejmount.com/wp-content/uploads/2020/01/26059903._SY475_.jpg?resize=316%2C475&ssl=1)
O’Reilly Media is the grand-daddy of technical publishers, and any of its titles will be quality. (Disclaimer: I am a content provider on contract to O’Reilly, and am damn proud of it.)
Creating a Data-Driven Organization is a solid primer to analytics adoption. As a manager, you’ll learn how to articulate a vision of data-savviness at your organization, and ask the right questions to help your staff get there.
This book moves seamlessly across the major components of a data culture: from data collection, to KPIs, even into ethics and privacy. You can consider this your handbook to what decisions need to be made for a successful analytics adoption.
2. Winning with Data
![Winning with data book cover](https://i0.wp.com/georgejmount.com/wp-content/uploads/2020/01/30305946._SY475_.jpg?resize=328%2C496&ssl=1)
While Creating a Data-Driven Organization thrives as an introduction to the what, Winning with Data thrives at the how and the how not.
Lots can go wrong with analytics adoption, as you might have inferred from the above HBR article. This book serves as a post-mortem of sorts: I particularly enjoyed the image of a “data breadline” which the authors painted early on, with organizations existing hand-to-mouth on the division between data have’s and have-not’s.
It’s easy for analytics strategy to devolve into hand-waving: use the right terms, rename a department something cool like “Center for Radical Experimentation,” and voilà! Analytics.
While you as a manager can’t be expected to serve as a technical expert, you should understand that your team needs substantial resources to do analytics right. Adding “data-driven” to the mission statement is not enough: you need to back it up with investments in both capital and labor.
3. Teaching Tech Together
![Teaching tech together book cover](https://external-content.duckduckgo.com/iu/?u=https%3A%2F%2Fimages.tandf.co.uk%2Fcommon%2Fjackets%2Famazon%2F978036735%2F9780367352974.jpg&f=1&nofb=1)
(This is the one that you can skim.)
Earlier I mentioned that analytics adoption takes significant labor investments. Look, for example, at Amazon’s Upskilling 2025 initiative. If Amazon is spending significantly to train its workers to analyze data, maybe you should, too.
Training plays significantly into a successful analytics adoption, so I recommend skimming this book as an example of what good technology training should look like. Teaching Tech Together is one of the few sources I know aimed at showing how to teach high-level digital literacy.
Again, I don’t expect you as a manager to become a subject matter expert, or a data educator. However, you should be able to spot quality upskilling resources for your organization. Without resources to learn and grow at your organization, employees will find them individually — and leave your organization.
4. Stringfest Analytics Resource Library
![](https://i0.wp.com/georgejmount.com/wp-content/uploads/2020/05/RGB-MAIN-LOGO-STRINGFEST-01-2-1024x751.jpg?resize=1024%2C751&ssl=1)
All right, this one isn’t a book, but it’s still got lots of information for you.
After reading, or at least skimming, these books, you will have seen that improving at analytics takes an organization-wide investment in capital and labor. My ultimate recommendation for you is to build a data upskilling academy at your organization.
I want to be transparent with what this would look like, so I have developed a resource library for data analytics training. This will have workshop outlines, demo notes and slide decks. Consider this my attempt to open-source what a data academy looks like.
The library is yours to use as you see fit: just subscribe below and it will be sent to you.
What did you think of these titles? What other titles have inspired your thinking on analytics culture & adoption? Let’s talk in the comments.
Interesting to think about data from an organizational perspective. These are going on my Christmas wish-list
Thanks for reading, they are some good ones! The last one is available for free online but hard copies are nice.